Frontiers in Physiology

Journal: Frontiers in Physiology

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Front Physiol

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Frontiers Media

ISSN

1664-042X

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Publications 1 - 10 of 68

No critical peripheral fatigue threshold during intermittent isometric time to task failure test with the knee extensors
Froyd, Christian; Beltrami, Fernando G.; Millet, Guillaume Y.; et al. (2016)
Frontiers in Physiology
It has been proposed that group III and IV muscle afferents provide inhibitory feedback from locomotor muscles to the central nervous system, setting an absolute threshold for the development of peripheral fatigue during exercise. The aim of this study was to test the validity of this theory. Thus, we asked whether the level of developed peripheral fatigue would differ when two consecutive exercise trials were completed to task failure. Ten trained sport students performed two exercise trials to task failure on an isometric dynamometer, allowing peripheral fatigue to be assessed 2 s after maximal voluntary contraction (MVC) post task failure. The trials, separated by 8 min, consisted of repeated sets of 10 × 5-s isometric knee extension followed by 5-s rest between contractions. In each set, the first nine contractions were performed at a target force at 60% of the pre-exercise MVC, while the 10th contraction was a MVC. MVC and evoked force responses to supramaximal electrical femoral nerve stimulation on relaxed muscles were assessed during the trials and at task failure. Stimulations at task failure consisted of single stimulus (SS), paired stimuli at 10 Hz (PS10), paired stimuli at 100 Hz (PS100), and 50 stimuli at 100 Hz (tetanus). Time to task failure for the first trial (12.84 ± 5.60 min) was longer (P < 0.001) than for the second (5.74 ± 1.77 min). MVC force was significantly lower at task failure for both trials compared with the pre-exercise values (both P < 0.001), but there were no differences in MVC at task failure in the first and second trials (P = 1.00). However, evoked peak force for SS, PS100, and tetanus were all reduced more at task failure in the second compared to the first trial (P = 0.014 for SS, P < 0.001 for PS100 and tetanus). These results demonstrate that subjects do not terminate exercise at task failure because they have reached a critical threshold in peripheral fatigue. The present data therefore question the existence of a critical peripheral fatigue threshold during intermittent isometric exercise to task failure with the knee extensors.
Reintroducing Heart Sounds for Early Detection of Acute Myocardial Ischemia in a Porcine Model – Correlation of Acoustic Cardiography With Gold Standard of Pressure-Volume Analysis
Luciani, Marco; Saccocci, Matteo; Kuwata, Shingo; et al. (2019)
Frontiers in Physiology
Background: Acoustic cardiography is a hybrid technique that couples heart sounds recording with ECG providing insights into electrical-mechanical activity of the heart in an unsupervised, non-invasive and inexpensive manner. During myocardial ischemia hemodynamic abnormalities appear in the first minutes and we hypothesize a putative diagnostic role of acoustic cardiography for prompt detection of cardiac dysfunction for future patient management improvement. Methods and Results: Ten female Swiss large white pigs underwent permanent distal coronary occlusion as a model of acute myocardial ischemia. Acoustic cardiography analyses were performed prior, during and after coronary occlusion. Pressure-volume analysis was conducted in parallel as an invasive method of hemodynamic assessment for comparison. Similar systolic and diastolic intervals obtained with the two techniques were significantly correlated [Q to min dP/dt vs. Q to second heart sound (r2 = 0.9583, p < 0.0001), PV diastolic filling time vs. AC perfusion time (r2 = 0.9686, p < 0.0001)]. Indexes of systolic and diastolic impairment correlated with quantifiable features of heart sounds [Tau vs. fourth heart sound Display Value (r2 = 0.2721, p < 0.0001) cardiac output vs. third heart sound Display Value (r2 = 0.0791 p = 0.0023)]. Additionally, acoustic cardiography diastolic time (AUC 0.675, p = 0.008), perfusion time (AUC 0.649, p = 0.024) and third heart sound Display Value (AUC 0.654, p = 0.019) emerged as possible indicators of coronary occlusion. Finally, these three parameters, when joined with heart rate into a composite joint-index, represent the best model in our experience for ischemia detection (AUC 0.770, p < 0.001). Conclusion: In the rapidly evolving setting of acute myocardial ischemia, acoustic cardiography provided meaningful insights of mechanical dysfunction in a prompt and non-invasive manner. These findings should propel interest in resurrecting this technique for future translational studies as well as reconsidering its reintroduction in the clinical setting.
The Relation Between Capillary Transit Times and Hemoglobin Saturation Heterogeneity
Lücker, Adrien; Secomb, Timothy W.; Weber, Bruno; et al. (2018)
Frontiers in Physiology
Capillary dysfunction impairs oxygen supply to parenchymal cells and often occurs in Alzheimer's disease, diabetes and aging. Disturbed capillary flow patterns have been shown to limit the efficacy of oxygen extraction and can be quantified using capillary transit time heterogeneity (CTH). However, the transit time of red blood cells (RBCs) through the microvasculature is not a direct measure of their capacity for oxygen delivery. Here we examine the relation between CTH and capillary outflow saturation heterogeneity (COSH), which is the heterogeneity of blood oxygen content at the venous end of capillaries. Models for the evolution of hemoglobin saturation heterogeneity (HSH) in capillary networks were developed and validated using a computational model with moving RBCs. Two representative situations were selected: a Krogh cylinder geometry with heterogeneous hemoglobin saturation (HS) at the inflow, and a parallel array of four capillaries. The heterogeneity of HS after converging capillary bifurcations was found to exponentially decrease with a time scale of 0.15–0.21 s due to diffusive interaction between RBCs. Similarly, the HS difference between parallel capillaries also drops exponentially with a time scale of 0.12–0.19 s. These decay times are substantially smaller than measured RBC transit times and only weakly depend on the distance between microvessels. This work shows that diffusive interaction strongly reduces COSH on a small spatial scale. Therefore, we conclude that CTH influences COSH yet does not determine it. The second part of this study will focus on simulations in microvascular networks from the rodent cerebral cortex. Actual estimates of COSH and CTH will then be given.
Dysfunctional LAT2 Amino Acid Transporter Is Associated With Cataract in Mouse and Humans
Knopfel, Emilia Boiadjieva; Vilches, Clara; Camargo, Simone M. R.; et al. (2019)
Frontiers in Physiology
Cataract, the loss of ocular lens transparency, accounts for ∼50% of worldwide blindness and has been associated with water and solute transport dysfunction across lens cellular barriers. We show that neutral amino acid antiporter LAT2 (Slc7a8) and uniporter TAT1 (Slc16a10) are expressed on mouse ciliary epithelium and LAT2 also in lens epithelium. Correspondingly, deletion of LAT2 induced a dramatic decrease in lens essential amino acid levels that was modulated by TAT1 defect. Interestingly, the absence of LAT2 led to increased incidence of cataract in mice, in particular in older females, and a synergistic effect was observed with simultaneous lack of TAT1. Screening SLC7A8 in patients diagnosed with congenital or age-related cataract yielded one homozygous single nucleotide deletion segregating in a family with congenital cataract. Expressed in HeLa cells, this LAT2 mutation did not support amino acid uptake. Heterozygous LAT2 variants were also found in patients with cataract some of which showed a reduced transport function when expressed in HeLa cells. Whether heterozygous LAT2 variants may contribute to the pathology of cataract needs to be further investigated. Overall, our results suggest that defects of amino acid transporter LAT2 are implicated in cataract formation, a situation that may be aggravated by TAT1 defects.
Distinctive steady-state heart rate and blood pressure responses to passive robotic leg exercise and functional electrical stimulation during head-up tilt
Sarabadani Tafreshi, Amirehsan; Riener, Robert; Klamroth-Marganska, Verena (2016)
Frontiers in Physiology
Introduction: Tilt tables enable early mobilization of patients by providing verticalization. But there is a high risk of orthostatic hypotension provoked by verticalization, especially after neurological diseases such as spinal cord injury. Robot-assisted tilt tables might be an alternative as they add passive robotic leg exercise (PE) that can be enhanced with functional electrical stimulation (FES) to the verticalization, thus reducing the risk of orthostatic hypotension. We hypothesized that the influence of PE on the cardiovascular system during verticalization (i.e., head-up tilt) depends on the verticalization angle, and FES strengthens the PE influence. To test our hypotheses, we investigated the PE effects on the cardiovascular parameters heart rate (HR), and systolic and diastolic blood pressures (sBP, dBP) at different angles of verticalization in a healthy population. Methods: Ten healthy subjects on a robot-assisted tilt table underwent four different study protocols while HR, sBP, and dBP were measured: (1) head-up tilt to 60° and 71° without PE; (2) PE at 20°, 40°, and 60° of head-up tilt; (3) PE while constant FES intensity was applied to the leg muscles, at 20°, 40°, and 60° of head-up tilt; (4) PE with variation of the applied FES intensity at 0°, 20°, 40°, and 60° of head-up tilt. Linear mixed models were used to model changes in HR, sBP, and dBP responses. Results: The models show that: (1) head-up tilt alone resulted in statistically significant increases in HR and dBP, but no change in sBP. (2) PE during head-up tilt resulted in statistically significant changes in HR, sBP, and dBP, but not at each angle and not always in the same direction (i.e., increase or decrease of cardiovascular parameters). Neither adding (3) FES at constant intensity to PE nor (4) variation of FES intensity during PE had any statistically significant effects on the cardiovascular parameters. Conclusion: The effect of PE on the cardiovascular system during head-up tilt is strongly dependent on the verticalization angle. Therefore, we conclude that orthostatic hypotension cannot be prevented by PE alone, but that the preventive effect depends on the verticalization angle of the robot-assisted tilt table. FES (independent of intensity) is not an important contributing factor to the PE effect.
Skin Temperature Measurement Using Contact Thermometry: A Systematic Review of Setup Variables and Their Effects on Measured Values
MacRae, Braid A.; Annaheim, Simon; Spengler, Christina M.; et al. (2018)
Frontiers in Physiology
Corrigendum: Acute Exercise-Induced Oxidative Stress Does Not Affect Immediate or Delayed Precursor Cell Mobilization in Healthy Young Males
Schmid, Michelle; Gruber, Hans-Jürgen; Kröpfl, Julia M.; et al. (2021)
Frontiers in Physiology
Blood pressure stratification using photoplethysmography and light gradient boosting machine
Hu, Xudong; Yin, Shimin; Zhang, Xizhuang; et al. (2023)
Frontiers in Physiology
Introduction: Globally, hypertension (HT) is a substantial risk factor for cardiovascular disease and mortality; hence, rapid identification and treatment of HT is crucial. In this study, we tested the light gradient boosting machine (LightGBM) machine learning method for blood pressure stratification based on photoplethysmography (PPG), which is used in most wearable devices. Methods: We used 121 records of PPG and arterial blood pressure (ABP) signals from the Medical Information Mart for Intensive Care III public database. PPG, velocity plethysmography, and acceleration plethysmography were used to estimate blood pressure; the ABP signals were used to determine the blood pressure stratification categories. Seven feature sets were established and used to train the Optuna-tuned LightGBM model. Three trials compared normotension (NT) vs. prehypertension (PHT), NT vs. HT, and NT + PHT vs. HT. Results: The F1 scores for these three classification trials were 90.18%, 97.51%, and 92.77%, respectively. The results showed that combining multiple features from PPG and its derivative led to a more accurate classification of HT classes than using features from only the PPG signal. Discussion: The proposed method showed high accuracy in stratifying HT risks, providing a noninvasive, rapid, and robust method for the early detection of HT, with promising applications in the field of wearable cuffless blood pressure measurement.
Fatigue Monitoring Through Wearables: A State-of-the-Art Review
Adão Martins, Neusa R.; Annaheim, Simon; Spengler, Christina M.; et al. (2021)
Frontiers in Physiology
The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems represent highly promising solutions for fatigue monitoring as they enable continuous, long-term monitoring of biomedical signals in unattended settings, with the required comfort and non-intrusiveness. This is a p rerequisite for the development of accurate models for fatigue monitoring in real-time. However, monitoring fatigue through wearable devices imposes unique challenges. To provide an overview of the current state-of-the-art in monitoring variables associated with fatigue via wearables and to detect potential gaps and pitfalls in current knowledge, a systematic review was performed. The Scopus and PubMed databases were searched for articles published in English since 2015, having the terms “fatigue,” “drowsiness,” “vigilance,” or “alertness” in the title, and proposing wearable device-based systems for non-invasive fatigue quantification. Of the 612 retrieved articles, 60 satisfied the inclusion criteria. Included studies were mainly of short duration and conducted in laboratory settings. In general, researchers developed fatigue models based on motion (MOT), electroencephalogram (EEG), photoplethysmogram (PPG), electrocardiogram (ECG), galvanic skin response (GSR), electromyogram (EMG), skin temperature (Tsk), eye movement (EYE), and respiratory (RES) data acquired by wearable devices available in the market. Supervised machine learning models, and more specifically, binary classification models, are predominant among the proposed fatigue quantification approaches. These models were considered to perform very well in detecting fatigue, however, little effort was made to ensure the use of high-quality data during model development. Together, the findings of this review reveal that methodological limitations have hindered the generalizability and real-world applicability of most of the proposed fatigue models. Considerably more work is needed to fully explore the potential of wearables for fatigue quantification as well as to better understand the relationship between fatigue and changes in physiological variables.
Classification of functional and non-functional arm use by inertial measurement units in individuals with upper limb impairment after stroke
Pohl, Johannes; Ryser, Alain; Veerbeek, Janne M.; et al. (2022)
Frontiers in Physiology
Background: Arm use metrics derived from wrist-mounted movement sensors are widely used to quantify the upper limb performance in real-life conditions of individuals with stroke throughout motor recovery. The calculation of real-world use metrics, such as arm use duration and laterality preferences, relies on accurately identifying functional movements. Hence, classifying upper limb activity into functional and non-functional classes is paramount. Acceleration thresholds are conventionally used to distinguish these classes. However, these methods are challenged by the high inter and intra-individual variability of movement patterns. In this study, we developed and validated a machine learning classifier for this task and compared it to methods using conventional and optimal thresholds. Methods: Individuals after stroke were video-recorded in their home environment performing semi-naturalistic daily tasks while wearing wrist-mounted inertial measurement units. Data were labeled frame-by-frame following the Taxonomy of Functional Upper Limb Motion definitions, excluding whole-body movements, and sequenced into 1-s epochs. Actigraph counts were computed, and an optimal threshold for functional movement was determined by receiver operating characteristic curve analyses on group and individual levels. A logistic regression classifier was trained on the same labels using time and frequency domain features. Performance measures were compared between all classification methods. Results: Video data (6.5 h) of 14 individuals with mild-to-severe upper limb impairment were labeled. Optimal activity count thresholds were ≥20.1 for the affected side and ≥38.6 for the unaffected side and showed high predictive power with an area under the curve (95% CI) of 0.88 (0.87,0.89) and 0.86 (0.85, 0.87), respectively. A classification accuracy of around 80% was equivalent to the optimal threshold and machine learning methods and outperformed the conventional threshold by ∼10%. Optimal thresholds and machine learning methods showed superior specificity (75–82%) to conventional thresholds (58–66%) across unilateral and bilateral activities. Conclusion: This work compares the validity of methods classifying stroke survivors’ real-life arm activities measured by wrist-worn sensors excluding whole-body movements. The determined optimal thresholds and machine learning classifiers achieved an equivalent accuracy and higher specificity than conventional thresholds. Our open-sourced classifier or optimal thresholds should be used to specify the intensity and duration of arm use.

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